河南水利与南水北调2024，Vol.53Issue(5)：34-35,2.
神经网络算法在传统水文模型洪水预报中的应用
Application of Neural Network Algorithms to Flood Forecasting Using Traditional Hydrological Models
李燕 1杨栋丹1
作者信息
- 1. 陕西省商南县应急管理局,陕西 商南 726300
- 折叠
摘要
Abstract
In order to forecast flood accurately and reduce the loss caused by flood disaster every year.In this paper,a hydrological model that combines the BP neural network algorithm with the semi-distributed Xin'Anjiang(XAJ)model is proposed.The one-cycle correction and real-time correction are tested with a practical case.The results show that the improved hydrological model incorporating BP neural network into the traditional hydrological model can correct the prediction error of the Xin'anjiang model,improve prediction accuracy,and shorten the correction calculation time,which has certain application value.关键词
洪水预报/BP神经网络/新安江模型/单周期校正/实时校正Key words
flood forecast/BP neural network/xin'Anjiang model/one-cycle correction/real-time correction分类
计算机与自动化引用本文复制引用
李燕,杨栋丹..神经网络算法在传统水文模型洪水预报中的应用[J].河南水利与南水北调,2024,53(5):34-35,2.
